| Conditions | 12 | 
| Total Lines | 58 | 
| Code Lines | 32 | 
| Lines | 58 | 
| Ratio | 100 % | 
| Changes | 0 | ||
Small methods make your code easier to understand, in particular if combined with a good name. Besides, if your method is small, finding a good name is usually much easier.
For example, if you find yourself adding comments to a method's body, this is usually a good sign to extract the commented part to a new method, and use the comment as a starting point when coming up with a good name for this new method.
Commonly applied refactorings include:
If many parameters/temporary variables are present:
Complex classes like glances.exports.glances_influxdb.Export._normalize() often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | #  | 
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| 88 | def export(self, name, columns, points):  | 
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| 89 | """Write the points to the InfluxDB server."""  | 
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| 90 | # Manage prefix  | 
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| 91 | if self.prefix is not None:  | 
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| 92 | name = self.prefix + "." + name  | 
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| 93 | # Write input to the InfluxDB database  | 
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| 94 | if not points:  | 
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| 95 |             logger.debug(f"Cannot export empty {name} stats to InfluxDB") | 
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| 96 | else:  | 
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| 97 | try:  | 
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| 98 | self.client.write_points(  | 
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| 99 | self.normalize_for_influxdb(name, columns, points),  | 
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| 100 | time_precision="s",  | 
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| 101 | )  | 
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| 102 | except Exception as e:  | 
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| 103 | # Log level set to warning instead of error (see: issue #1561)  | 
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| 104 |                 logger.warning(f"Cannot export {name} stats to InfluxDB ({e})") | 
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| 105 | else:  | 
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| 106 |                 logger.debug(f"Export {name} stats to InfluxDB") | 
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| 107 |